JOURNAL ARTICLE

Shape and property identification of an elastic inclusion via a full waveform inversion and adjoint method.

  • Published In: Journal of Theoretical & Computational Acoustics, 2025, v. 33, n. 3. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Sayag, Amit; Givoli, Dan 3 of 3

Abstract

The problem of identifying the precise shape and material properties of a soft inclusion in a two-dimensional elastic medium is considered. The identification is performed based on time-dependent displacement response to a given wave source, measured by sensors at discrete locations. "Inclusion" here means an unknown local region whose material properties differ significantly from those of the background medium, which are assumed to be known. Applications include identification of unknown scatterers in solid earth geophysics and non-destructive testing of structures. The identification method is based on Full Waveform Inversion (FWI) and an adjoint scheme. In a previous publication, a precise shape identification method was developed for a cavity of an arbitrary shape in an acoustic medium (or a hole in a membrane). The present paper extends this publication in three ways. First, the medium is elastic rather than acoustic. Second, the scatterer is an inclusion rather then a cavity (the latter can be regarded as the limiting case of an inclusion). Third, an attempt is made to identify both the precise shape and the material properties of the inclusion, simultaneously. This attempt is only partly successful, and the reasons for this are analyzed. Numerical examples are used to demonstrate the proposed methodology. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Theoretical & Computational Acoustics. 2025/09, Vol. 33, Issue 3, p1
  • Document Type:Article
  • Subject Area:Physics
  • Publication Date:2025
  • ISSN:2591-7285
  • DOI:10.1142/S2591728525500045
  • Accession Number:187573047
  • Copyright Statement:Copyright of Journal of Theoretical & Computational Acoustics is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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